Search Results for author: Danda Pani Paudel

Found 91 papers, 39 papers with code

Exploration-Driven Generative Interactive Environments

1 code implementation3 Apr 2025 Nedko Savov, Naser Kazemi, Mohammad Mahdi, Danda Pani Paudel, Xi Wang, Luc van Gool

To this end, we annotate the behavior and controls of 974 virtual environments - a dataset that we name RetroAct.

Benchmarking Multi-modal Semantic Segmentation under Sensor Failures: Missing and Noisy Modality Robustness

1 code implementation24 Mar 2025 Chenfei Liao, Kaiyu Lei, Xu Zheng, Junha Moon, Zhixiong Wang, YiXuan Wang, Danda Pani Paudel, Luc van Gool, Xuming Hu

We then introduce a robustness benchmark that evaluates MMSS models under three scenarios: Entire-Missing Modality (EMM), Random-Missing Modality (RMM), and Noisy Modality (NM).

Avg Benchmarking +1

SceneSplat: Gaussian Splatting-based Scene Understanding with Vision-Language Pretraining

1 code implementation23 Mar 2025 Yue Li, Qi Ma, Runyi Yang, Huapeng Li, Mengjiao Ma, Bin Ren, Nikola Popovic, Nicu Sebe, Ender Konukoglu, Theo Gevers, Luc van Gool, Martin R. Oswald, Danda Pani Paudel

In order to power the proposed methods, we introduce SceneSplat-7K, the first large-scale 3DGS dataset for indoor scenes, comprising of 6868 scenes derived from 7 established datasets like ScanNet, Matterport3D, etc.

3DGS Benchmarking +2

Dream to Drive: Model-Based Vehicle Control Using Analytic World Models

no code implementations14 Feb 2025 Asen Nachkov, Danda Pani Paudel, Jan-Nico Zaech, Davide Scaramuzza, Luc van Gool

Differentiable simulators have recently shown great promise for training autonomous vehicle controllers.

Understanding the World's Museums through Vision-Language Reasoning

no code implementations2 Dec 2024 Ada-Astrid Balauca, Sanjana Garai, Stefan Balauca, Rasesh Udayakumar Shetty, Naitik Agrawal, Dhwanil Subhashbhai Shah, Yuqian Fu, Xi Wang, Kristina Toutanova, Danda Pani Paudel, Luc van Gool

In this work, we facilitate such reasoning by (a) collecting and curating a large-scale dataset of 65M images and 200M question-answer pairs in the standard museum catalog format for exhibits from all around the world; (b) training large vision-language models on the collected dataset; (c) benchmarking their ability on five visual question answering tasks.

Benchmarking Question Answering +1

Holistic Understanding of 3D Scenes as Universal Scene Description

no code implementations2 Dec 2024 Anna-Maria Halacheva, Yang Miao, Jan-Nico Zaech, Xi Wang, Luc van Gool, Danda Pani Paudel

In this work, we address this shortcoming and introduce (1) an expertly curated dataset in the Universal Scene Description (USD) format, featuring high-quality manual annotations, for instance, segmentation and articulation on 280 indoor scenes; (2) a learning-based model together with a novel baseline capable of predicting part segmentation along with a full specification of motion attributes, including motion type, articulated and interactable parts, and motion parameters; (3) a benchmark serving to compare upcoming methods for the task at hand.

Instance Segmentation Mixed Reality +2

Occam's LGS: A Simple Approach for Language Gaussian Splatting

no code implementations2 Dec 2024 Jiahuan Cheng, Jan-Nico Zaech, Luc van Gool, Danda Pani Paudel

A major reason for the success of 3DGS is its simplicity of representing a scene with a set of Gaussians, which makes it easy to interpret and adapt.

3DGS 3D Reconstruction +1

ObjectRelator: Enabling Cross-View Object Relation Understanding in Ego-Centric and Exo-Centric Videos

no code implementations28 Nov 2024 Yuqian Fu, Runze Wang, Yanwei Fu, Danda Pani Paudel, Xuanjing Huang, Luc van Gool

In this paper, we focus on the Ego-Exo Object Correspondence task, an emerging challenge in the field of computer vision that aims to map objects across ego-centric and exo-centric views.

Object Object Localization +1

RobustFormer: Noise-Robust Pre-training for images and videos

no code implementations20 Nov 2024 Ashish Bastola, Nishant Luitel, Hao Wang, Danda Pani Paudel, Roshani Poudel, Abolfazl Razi

While deep learning models are powerful tools that revolutionized many areas, they are also vulnerable to noise as they rely heavily on learning patterns and features from the exact details of the clean data.

EvenNICER-SLAM: Event-based Neural Implicit Encoding SLAM

no code implementations4 Oct 2024 Shi Chen, Danda Pani Paudel, Luc van Gool

The advancement of dense visual simultaneous localization and mapping (SLAM) has been greatly facilitated by the emergence of neural implicit representations.

Simultaneous Localization and Mapping

ReVLA: Reverting Visual Domain Limitation of Robotic Foundation Models

no code implementations23 Sep 2024 Sombit Dey, Jan-Nico Zaech, Nikolay Nikolov, Luc van Gool, Danda Pani Paudel

This is potentially caused by limited variations in the training data and/or catastrophic forgetting, leading to domain limitations in the vision foundation models.

Autonomous Vehicle Controllers From End-to-End Differentiable Simulation

no code implementations12 Sep 2024 Asen Nachkov, Danda Pani Paudel, Luc van Gool

In this work, we leverage a differentiable simulator and design an analytic policy gradients (APG) approach to training AV controllers on the large-scale Waymo Open Motion Dataset.

Autonomous Vehicles Behavioural cloning

Taming CLIP for Fine-grained and Structured Visual Understanding of Museum Exhibits

1 code implementation3 Sep 2024 Ada-Astrid Balauca, Danda Pani Paudel, Kristina Toutanova, Luc van Gool

In this work, we aim to adapt CLIP for fine-grained and structured -- in the form of tabular data -- visual understanding of museum exhibits.

Attribute

A Simple and Generalist Approach for Panoptic Segmentation

no code implementations29 Aug 2024 Nedyalko Prisadnikov, Wouter Van Gansbeke, Danda Pani Paudel, Luc van Gool

These contributions are: (i) a positional-embedding (PE) based loss for improved centroid regressions; (ii) Edge Distance Sampling (EDS) for the better separation of instance boundaries.

Missing Labels Panoptic Segmentation

ShapeSplat: A Large-scale Dataset of Gaussian Splats and Their Self-Supervised Pretraining

no code implementations20 Aug 2024 Qi Ma, Yue Li, Bin Ren, Nicu Sebe, Ender Konukoglu, Theo Gevers, Luc van Gool, Danda Pani Paudel

In particular, we show that (1) the distribution of the optimized GS centroids significantly differs from the uniformly sampled point cloud (used for initialization) counterpart; (2) this change in distribution results in degradation in classification but improvement in segmentation tasks when using only the centroids; (3) to leverage additional Gaussian parameters, we propose Gaussian feature grouping in a normalized feature space, along with splats pooling layer, offering a tailored solution to effectively group and embed similar Gaussians, which leads to notable improvement in finetuning tasks.

3DGS Representation Learning

iHuman: Instant Animatable Digital Humans From Monocular Videos

1 code implementation15 Jul 2024 Pramish Paudel, Anubhav Khanal, Ajad Chhatkuli, Danda Pani Paudel, Jyoti Tandukar

In this paper, we present a fast, simple, yet effective method for creating animatable 3D digital humans from monocular videos.

3D geometry 3D Reconstruction

Bringing Masked Autoencoders Explicit Contrastive Properties for Point Cloud Self-Supervised Learning

1 code implementation8 Jul 2024 Bin Ren, Guofeng Mei, Danda Pani Paudel, Weijie Wang, Yawei Li, Mengyuan Liu, Rita Cucchiara, Luc van Gool, Nicu Sebe

To answer this question, we first empirically validate that integrating MAE-based point cloud pre-training with the standard contrastive learning paradigm, even with meticulous design, can lead to a decrease in performance.

Contrastive Learning Data Augmentation +2

Implicit-Zoo: A Large-Scale Dataset of Neural Implicit Functions for 2D Images and 3D Scenes

1 code implementation25 Jun 2024 Qi Ma, Danda Pani Paudel, Ender Konukoglu, Luc van Gool

Neural implicit functions have demonstrated significant importance in various areas such as computer vision, graphics.

Image Classification NeRF +1

XTrack: Multimodal Training Boosts RGB-X Video Object Trackers

2 code implementations28 May 2024 Yuedong Tan, Zongwei Wu, Yuqian Fu, Zhuyun Zhou, Guolei Sun, Eduard Zamfi, Chao Ma, Danda Pani Paudel, Luc van Gool, Radu Timofte

Technically, we achieve this by routing samples from one modality to the expert of the others, within a mixture-of-experts framework designed for multimodal video object tracking.

Inductive Bias Multi-Label Classification +3

CaLDiff: Camera Localization in NeRF via Pose Diffusion

no code implementations23 Dec 2023 Rashik Shrestha, Bishad Koju, Abhigyan Bhusal, Danda Pani Paudel, François Rameau

This paper studies the problem of localizing cameras in NeRF using a diffusion model for camera pose adjustment.

Camera Localization NeRF

Ternary-Type Opacity and Hybrid Odometry for RGB NeRF-SLAM

no code implementations20 Dec 2023 Junru Lin, Asen Nachkov, Songyou Peng, Luc van Gool, Danda Pani Paudel

In this work, we address the challenge of deploying Neural Radiance Field (NeRFs) in Simultaneous Localization and Mapping (SLAM) under the condition of lacking depth information, relying solely on RGB inputs.

NeRF Simultaneous Localization and Mapping +1

Model-aware 3D Eye Gaze from Weak and Few-shot Supervisions

1 code implementation20 Nov 2023 Nikola Popovic, Dimitrios Christodoulou, Danda Pani Paudel, Xi Wang, Luc van Gool

In this work, we propose to predict 3D eye gaze from weak supervision of eye semantic segmentation masks and direct supervision of a few 3D gaze vectors.

Semantic Segmentation

Deformable Neural Radiance Fields using RGB and Event Cameras

no code implementations ICCV 2023 Qi Ma, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool

In this work, we develop a novel method to model the deformable neural radiance fields using RGB and event cameras.

Prior Based Online Lane Graph Extraction from Single Onboard Camera Image

no code implementations25 Jul 2023 Yigit Baran Can, Alexander Liniger, Danda Pani Paudel, Luc van Gool

Thus, online estimation of the lane graph is crucial for widespread and reliable autonomous navigation.

Autonomous Navigation

Improving Online Lane Graph Extraction by Object-Lane Clustering

no code implementations ICCV 2023 Yigit Baran Can, Alexander Liniger, Danda Pani Paudel, Luc van Gool

In this work, we propose an architecture and loss formulation to improve the accuracy of local lane graph estimates by using 3D object detection outputs.

3D Object Detection Autonomous Driving +4

Online Lane Graph Extraction from Onboard Video

no code implementations3 Apr 2023 Yigit Baran Can, Alexander Liniger, Danda Pani Paudel, Luc van Gool

One of the most common and useful representation of such an understanding is done in the form of BEV lane graphs.

Autonomous Driving Navigate

NeRF-GAN Distillation for Efficient 3D-Aware Generation with Convolutions

1 code implementation22 Mar 2023 Mohamad Shahbazi, Evangelos Ntavelis, Alessio Tonioni, Edo Collins, Danda Pani Paudel, Martin Danelljan, Luc van Gool

Pose-conditioned convolutional generative models struggle with high-quality 3D-consistent image generation from single-view datasets, due to their lack of sufficient 3D priors.

Image Generation Inductive Bias +1

Surface Normal Clustering for Implicit Representation of Manhattan Scenes

1 code implementation ICCV 2023 Nikola Popovic, Danda Pani Paudel, Luc van Gool

In this work, we aim to leverage the geometric prior of Manhattan scenes to improve the implicit neural radiance field representations.

Clustering NeRF +1

Robust RGB-D Fusion for Saliency Detection

1 code implementation2 Aug 2022 Zongwei Wu, Shriarulmozhivarman Gobichettipalayam, Brahim Tamadazte, Guillaume Allibert, Danda Pani Paudel, Cédric Demonceaux

In this work, we aim for RGB-D saliency detection that is robust to the low-quality depths which primarily appear in two forms: inaccuracy due to noise and the misalignment to RGB.

Saliency Detection

Gradient Obfuscation Checklist Test Gives a False Sense of Security

no code implementations3 Jun 2022 Nikola Popovic, Danda Pani Paudel, Thomas Probst, Luc van Gool

It has since become a trend to use these five characteristics as a sufficient test, to determine whether or not gradient obfuscation is the main source of robustness.

Spatially Multi-conditional Image Generation

no code implementations25 Mar 2022 Ritika Chakraborty, Nikola Popovic, Danda Pani Paudel, Thomas Probst, Luc van Gool

However, multi-conditional image generation is a very challenging problem due to the heterogeneity and the sparsity of the (in practice) available conditioning labels.

Conditional Image Generation Missing Labels

Transforming Model Prediction for Tracking

1 code implementation CVPR 2022 Christoph Mayer, Martin Danelljan, Goutam Bhat, Matthieu Paul, Danda Pani Paudel, Fisher Yu, Luc van Gool

Optimization based tracking methods have been widely successful by integrating a target model prediction module, providing effective global reasoning by minimizing an objective function.

Inductive Bias model +3

Unsupervised Domain Adaptation for Nighttime Aerial Tracking

2 code implementations CVPR 2022 Junjie Ye, Changhong Fu, Guangze Zheng, Danda Pani Paudel, Guang Chen

Previous advances in object tracking mostly reported on favorable illumination circumstances while neglecting performance at nighttime, which significantly impeded the development of related aerial robot applications.

Object Discovery Object Tracking +1

Collapse by Conditioning: Training Class-conditional GANs with Limited Data

1 code implementation ICLR 2022 Mohamad Shahbazi, Martin Danelljan, Danda Pani Paudel, Luc van Gool

On the contrary, we observe that class-conditioning causes mode collapse in limited data settings, where unconditional learning leads to satisfactory generative ability.

Generative Adversarial Network

Improving the Behaviour of Vision Transformers with Token-consistent Stochastic Layers

no code implementations30 Dec 2021 Nikola Popovic, Danda Pani Paudel, Thomas Probst, Luc van Gool

We use linear layers with token-consistent stochastic parameters inside the multilayer perceptron blocks, without altering the architecture of the transformer.

Adversarial Robustness Transfer Learning

End-to-End Learning of Multi-category 3D Pose and Shape Estimation

no code implementations19 Dec 2021 Yigit Baran Can, Alexander Liniger, Danda Pani Paudel, Luc van Gool

We use a Transformer-based architecture to detect the keypoints, as well as to summarize the visual context of the image.

Topology Preserving Local Road Network Estimation from Single Onboard Camera Image

1 code implementation CVPR 2022 Yigit Baran Can, Alexander Liniger, Danda Pani Paudel, Luc van Gool

We represent the road topology using a set of directed lane curves and their interactions, which are captured using their intersection points.

Structured Bird's-Eye-View Traffic Scene Understanding from Onboard Images

2 code implementations ICCV 2021 Yigit Baran Can, Alexander Liniger, Danda Pani Paudel, Luc van Gool

In this work, we study the problem of extracting a directed graph representing the local road network in BEV coordinates, from a single onboard camera image.

Autonomous Navigation Lane Detection +1

TACS: Taxonomy Adaptive Cross-Domain Semantic Segmentation

1 code implementation10 Sep 2021 Rui Gong, Martin Danelljan, Dengxin Dai, Danda Pani Paudel, Ajad Chhatkuli, Fisher Yu, Luc van Gool

In many real-world settings, the target domain task requires a different taxonomy than the one imposed by the source domain.

Contrastive Learning Domain Adaptation +1

GANmut: Learning Interpretable Conditional Space for Gamut of Emotions

no code implementations CVPR 2021 Stefano d'Apolito, Danda Pani Paudel, Zhiwu Huang, Andres Romero, Luc van Gool

On the other hand, learning from inexpensive and intuitive basic categorical emotion labels leads to limited emotion variability.

Learning to Relate Depth and Semantics for Unsupervised Domain Adaptation

1 code implementation CVPR 2021 Suman Saha, Anton Obukhov, Danda Pani Paudel, Menelaos Kanakis, Yuhua Chen, Stamatios Georgoulis, Luc van Gool

Specifically, we show that: (1) our approach improves performance on all tasks when they are complementary and mutually dependent; (2) the CTRL helps to improve both semantic segmentation and depth estimation tasks performance in the challenging UDA setting; (3) the proposed ISL training scheme further improves the semantic segmentation performance.

Monocular Depth Estimation Multi-Task Learning +4

Learning Target Candidate Association to Keep Track of What Not to Track

1 code implementation ICCV 2021 Christoph Mayer, Martin Danelljan, Danda Pani Paudel, Luc van Gool

To tackle the problem of lacking ground-truth correspondences between distractor objects in visual tracking, we propose a training strategy that combines partial annotations with self-supervision.

Video Object Tracking Visual Object Tracking +1

Unsupervised Robust Domain Adaptation without Source Data

no code implementations26 Mar 2021 Peshal Agarwal, Danda Pani Paudel, Jan-Nico Zaech, Luc van Gool

This paper aims at answering the question of finding the right strategy to make the target model robust and accurate in the setting of unsupervised domain adaptation without source data.

Image Classification Unsupervised Domain Adaptation

Unsupervised Monocular Depth Reconstruction of Non-Rigid Scenes

no code implementations31 Dec 2020 Ayça Takmaz, Danda Pani Paudel, Thomas Probst, Ajad Chhatkuli, Martin R. Oswald, Luc van Gool

In this work, we present an unsupervised monocular framework for dense depth estimation of dynamic scenes, which jointly reconstructs rigid and non-rigid parts without explicitly modelling the camera motion.

Depth Estimation Motion Segmentation

An Efficient Recurrent Adversarial Framework for Unsupervised Real-Time Video Enhancement

no code implementations24 Dec 2020 Dario Fuoli, Zhiwu Huang, Danda Pani Paudel, Luc van Gool, Radu Timofte

Video enhancement is a challenging problem, more than that of stills, mainly due to high computational cost, larger data volumes and the difficulty of achieving consistency in the spatio-temporal domain.

Video Enhancement

CompositeTasking: Understanding Images by Spatial Composition of Tasks

1 code implementation CVPR 2021 Nikola Popovic, Danda Pani Paudel, Thomas Probst, Guolei Sun, Luc van Gool

Learning to perform spatially distributed tasks is motivated by the frequent availability of only sparse labels across tasks, and the desire for a compact multi-tasking network.

Decoder

Cluster, Split, Fuse, and Update: Meta-Learning for Open Compound Domain Adaptive Semantic Segmentation

no code implementations CVPR 2021 Rui Gong, Yuhua Chen, Danda Pani Paudel, Yawei Li, Ajad Chhatkuli, Wen Li, Dengxin Dai, Luc van Gool

Open compound domain adaptation (OCDA) is a domain adaptation setting, where target domain is modeled as a compound of multiple unknown homogeneous domains, which brings the advantage of improved generalization to unseen domains.

Domain Adaptation Meta-Learning +2

Soft Contrastive Learning for Visual Localization

1 code implementation NeurIPS 2020 Janine Thoma, Danda Pani Paudel, Luc V. Gool

Our soft assignment makes a gradual distinction between close and far images in both geometric and feature spaces.

Contrastive Learning Image Retrieval +2

Facial Emotion Recognition with Noisy Multi-task Annotations

1 code implementation19 Oct 2020 Siwei Zhang, Zhiwu Huang, Danda Pani Paudel, Luc van Gool

In our formulation, we exploit a new method to enable the emotion prediction and the joint distribution learning in a unified adversarial learning game.

Facial Emotion Recognition

Learning Condition Invariant Features for Retrieval-Based Localization from 1M Images

1 code implementation27 Aug 2020 Janine Thoma, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool

Image features for retrieval-based localization must be invariant to dynamic objects (e. g. cars) as well as seasonal and daytime changes.

Retrieval Triplet

Self-Calibration Supported Robust Projective Structure-from-Motion

no code implementations4 Jul 2020 Rui Gong, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool

In this paper, we propose a unified SfM method, in which the matching process is supported by self-calibration constraints.

Camera Calibration valid

Geometrically Mappable Image Features

1 code implementation21 Mar 2020 Janine Thoma, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool

This is achieved by guiding the learning process such that the feature and geometric distances between images are directly proportional.

Image Retrieval Retrieval

Unsupervised Learning of Category-Specific Symmetric 3D Keypoints from Point Sets

1 code implementation ECCV 2020 Clara Fernandez-Labrador, Ajad Chhatkuli, Danda Pani Paudel, Jose J. Guerrero, Cédric Demonceaux, Luc van Gool

This paper aims at learning category-specific 3D keypoints, in an unsupervised manner, using a collection of misaligned 3D point clouds of objects from an unknown category.

Domain Agnostic Feature Learning for Image and Video Based Face Anti-spoofing

no code implementations15 Dec 2019 Suman Saha, Wen-Hao Xu, Menelaos Kanakis, Stamatios Georgoulis, Yu-Hua Chen, Danda Pani Paudel, Luc van Gool

Face anti-spoofing is a measure towards this direction for bio-metric user authentication, and in particular face recognition, that tries to prevent spoof attacks.

Face Anti-Spoofing Face Recognition

Convex Relaxations for Consensus and Non-Minimal Problems in 3D Vision

no code implementations ICCV 2019 Thomas Probst, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool

Notably, we further exploit the POP formulation of non-minimal solver also for the generic consensus maximization problems in 3D vision.

Sliced Wasserstein Generative Models

1 code implementation CVPR 2019 Jiqing Wu, Zhiwu Huang, Dinesh Acharya, Wen Li, Janine Thoma, Danda Pani Paudel, Luc van Gool

In generative modeling, the Wasserstein distance (WD) has emerged as a useful metric to measure the discrepancy between generated and real data distributions.

Image Generation Video Generation

Towards High Resolution Video Generation with Progressive Growing of Sliced Wasserstein GANs

1 code implementation4 Oct 2018 Dinesh Acharya, Zhiwu Huang, Danda Pani Paudel, Luc van Gool

Furthermore, we introduce a sliced version of Wasserstein GAN (SWGAN) loss to improve the distribution learning on the video data of high-dimension and mixed-spatiotemporal distribution.

Action Recognition Image Generation +2

Sampling Algebraic Varieties for Robust Camera Autocalibration

no code implementations ECCV 2018 Danda Pani Paudel, Luc van Gool

This paper addresses the problem of robustly autocalibrating a moving camera with constant intrinsics.

Incremental Non-Rigid Structure-from-Motion with Unknown Focal Length

no code implementations ECCV 2018 Thomas Probst, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool

In this paper we present a method for incremental Non-Rigid Structure-from-Motion (NRSfM) with the perspective camera model and the isometric surface prior with unknown focal length.

Model-free Consensus Maximization for Non-Rigid Shapes

no code implementations ECCV 2018 Thomas Probst, Ajad Chhatkuli, Danda Pani Paudel, Luc van Gool

In this paper, we formulate the model-free consensus maximization as an Integer Program in a graph using `rules' on measurements.

model

Face Translation between Images and Videos using Identity-aware CycleGAN

no code implementations4 Dec 2017 Zhiwu Huang, Bernhard Kratzwald, Danda Pani Paudel, Jiqing Wu, Luc van Gool

This paper presents a new problem of unpaired face translation between images and videos, which can be applied to facial video prediction and enhancement.

Image-to-Image Translation Translation +1

Improving Video Generation for Multi-functional Applications

1 code implementation30 Nov 2017 Bernhard Kratzwald, Zhiwu Huang, Danda Pani Paudel, Acharya Dinesh, Luc van Gool

In this paper, we aim to improve the state-of-the-art video generative adversarial networks (GANs) with a view towards multi-functional applications.

Colorization Future prediction +2

Optimal Transformation Estimation With Semantic Cues

no code implementations ICCV 2017 Danda Pani Paudel, Adlane Habed, Luc van Gool

This paper addresses the problem of estimating the geometric transformation relating two distinct visual modalities (e. g. an image and a map, or a projective structure and a Euclidean 3D model) while relying only on semantic cues, such as semantically segmented regions or object bounding boxes.

Consensus Maximization With Linear Matrix Inequality Constraints

no code implementations CVPR 2017 Pablo Speciale, Danda Pani Paudel, Martin R. Oswald, Till Kroeger, Luc van Gool, Marc Pollefeys

While randomized methods like RANSAC are fast, they do not guarantee global optimality and fail to manage large amounts of outliers.

Sliced Wasserstein Generative Models

1 code implementation8 Jun 2017 Jiqing Wu, Zhiwu Huang, Dinesh Acharya, Wen Li, Janine Thoma, Danda Pani Paudel, Luc van Gool

In generative modeling, the Wasserstein distance (WD) has emerged as a useful metric to measure the discrepancy between generated and real data distributions.

Image Generation Video Generation

Robust and Optimal Sum-of-Squares-Based Point-to-Plane Registration of Image Sets and Structured Scenes

no code implementations ICCV 2015 Danda Pani Paudel, Adlane Habed, Cedric Demonceaux, Pascal Vasseur

This paper deals with the problem of registering a known structured 3D scene and its metric Structure-from-Motion (SfM) counterpart.

LMI-Based 2D-3D Registration: From Uncalibrated Images to Euclidean Scene

no code implementations CVPR 2015 Danda Pani Paudel, Adlane Habed, Cedric Demonceaux, Pascal Vasseur

This paper investigates the problem of registering a scanned scene, represented by 3D Euclidean point coordinates, and two or more uncalibrated cameras.

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